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---
layout: page
hide_logo: true
---
<head>
<!-- Global site tag (gtag.js) - Google Analytics -->
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<title>secrier lab</title>
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<meta name="keywords" content="UCL, cancer, genomics, mutational signatures, computational biology, AI, cancer dormancy, quiescence, UCL Genetics Institute">
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<div class="bigtitle logobox" style="display:table-cell; vertical-align:middle">
Secrier Lab
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<strong>Computational Cancer Biology @ UCL Genetics Institute</strong>
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The Secrier lab at the <a class="off" href="https://www.ucl.ac.uk/biosciences/departments/gee/research-centres/genetics-institute"><strong>UCL Genetics Institute</strong></a> addresses fundamental questions on somatic evolution using cancer as a primary system of investigation, along two main axes: <br>
<br>
(1) How mutational processes shape cellular plasticity and intrinsic adaptation to stress; <br>
(2) How cells co-evolve with their microenvironmental niche to evade therapy and persist in the tissue. <br>
<br>
We are interested in understanding the mutational processes underlying cancer development and the cell state transitions that enable progression to advanced malignancy, as well as the role of the tumour microenvironment in this process.
To address such questions, we develop and apply cutting edge statistical modelling, data integration and machine learning methods to link bulk, single cell, spatial transcriptomics and digital pathology data.
The lab has been awarded a <b><a href="https://www.ucl.ac.uk/news/2020/oct/ucl-academics-named-future-leaders-fellows">UKRI Future Leaders Fellowship</a></b> to explore the mutational processes and spatial context of tumour dormancy.
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Selected papers
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<a class="off" href="https://pubmed.ncbi.nlm.nih.gov/37919776/">
Multi-scale characterisation of homologous recombination deficiency in breast cancer.
</a>
</div>
<div class="smallspacer"></div>
<div class="smallnote">
Jacobson et al, Genome Med 2023.
</div>
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<div class="note">
<i class="fa fa-file-text-o fa-fw"></i>
<a class="off" href="https://pubmed.ncbi.nlm.nih.gov/37860768/">
HistoMIL: A Python package for training multiple instance learning models on histopathology slides.
</a>
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<div class="smallnote">
Pan and Secrier. iScience 2023.
</div>
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<a class="off" href="https://pubmed.ncbi.nlm.nih.gov/37454136/">
Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma.
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<a class="off" href="https://pubmed.ncbi.nlm.nih.gov/37221612/">
Genomic hallmarks and therapeutic implications of G0 cell cycle arrest in cancer.
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Wiecek et al, Genome Biol 2023.
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<a class="off" href="https://www.nature.com/articles/s41467-023-36439-7">
Genomic and microenvironmental heterogeneity shaping epithelial-to-mesenchymal trajectories in cancer.
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<div class="smallnote">
Tagliazucci et al, Nat Commun 2023.
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<div class="note">
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<a class="off" href="https://pubmed.ncbi.nlm.nih.gov/27595477/">
Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance.
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</div>
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<div class="smallnote">
Secrier et al, Nat Genet 2016.
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Misc
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